Type-I Interferon Signaling in Fanconi Anemia
Bibliographic record
Abstract
Fanconi Anemia (FA) is a genome instability syndrome caused by mutations in one of the 23 repair genes of the Fanconi pathway. This heterogenous disease is usually characterized by congenital abnormalities, premature ageing and bone marrow failure. FA patients also show a high predisposition to hematological and solid cancers. The Fanconi pathway ensures the repair of interstrand crosslinks (ICLs) DNA damage. Defect in one of its proteins prevents functional DNA repair, leading to the accumulation of DNA breaks and genome instability. Accumulating evidence has documented a close relationship between genome instability and inflammation, including the production of type-I Interferon. In this context, type-I Interferon is produced upon activation of pattern recognition receptors by nucleic acids including by the cyclic GMP-AMP synthase (cGAS) that detects DNA. In mouse models of diseases displaying genome instability, type-I Interferon response is responsible for an important part of the pathological symptoms, including premature aging, short stature, and neurodegeneration. This is illustrated in mouse models of Ataxia-telangiectasia and Aicardi-Goutières Syndrome in which genetic depletion of either Interferon Receptor IFNAR, cGAS or STING relieves pathological symptoms. FA is also a genetic instability syndrome with symptoms such as premature aging and predisposition to cancer. In this review we will focus on the different molecular mechanisms potentially leading to type-I Interferon activation. A better understanding of the molecular mechanisms engaging type-I Interferon signaling in FA may ultimately lead to the discovery of new therapeutic targets to rescue the pathological inflammation and premature aging associated with Fanconi Anemia.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".